Remote Sensing and GIS for Monitoring Urbanization and Urban Health
Remote sensing technology and Geographic Information Systems (GIS) have made significant advancements in the field of urban health, playing crucial roles in monitoring and analyzing urban expansion, land cover changes, urban heat island effects, and flood simulation. These developments indicate that...
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| Materialtyp: | Online |
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| Språk: | engelska |
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MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Länkar: | ONIX_20250220_9783725828517_463 |
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| _version_ | 1869520021953183744 |
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| collection | Directory of Open Access Books |
| description | Remote sensing technology and Geographic Information Systems (GIS) have made significant advancements in the field of urban health, playing crucial roles in monitoring and analyzing urban expansion, land cover changes, urban heat island effects, and flood simulation. These developments indicate that the application of remote sensing and GIS in urban health is continuously deepening, providing powerful tools for urban planning and management. The aim of this reprint is to immerse the reader in the latest methodological models and applications of remote sensing, GIS, and big data in the fields of urban development, healthy cities, and environmental health. This reprint brings together the latest research findings from numerous scholars in the fields of environmental science, urban and rural planning, public health, remote sensing, and GIS applications. Innovations in data methods are evident in these studies, such as the introduction and application of dendrochronological data concepts and analytical methods. There is also research that integrates big data from the internet and various remote sensing data to study urban land use, transportation, public service facilities, and infectious diseases. The advancements in these areas indicate that the application of remote sensing and GIS in the field of urban health is continuously providing powerful tools for urban planning and management. As technology evolves, the application of these technologies in the field of urban health is expected to become more extensive and profound in the future. |
| format | Online |
| id | doab-20.500.12854ir-153099 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1530992025-02-20T13:33:27Z Remote Sensing and GIS for Monitoring Urbanization and Urban Health Li, Xinhu Du, Shihong Jia, Peng Gatzweiler, Franz W. Song, Jinchao bacterial foodborne disease global logistic regression geographically weighted logistic regression urban and rural areas vulnerability built environment human health air pollution GIS moderating effect building extraction semantic segmentation group normalization deformable convolution remote sensing images time ring data long time series spatio-temporal characteristics Amazon forest cover urban expansion nighttime light cellular automata urban growth shared socioeconomic pathways allometric scaling land-use change landslide hazard assessment remote sensing data XGBoost algorithm highway pre-trained model night-time lights Google Aggregated Mobility Research Dataset human mobility Africa rural and urban classification GEE RSEI ecological environmental quality Lhasa–Nyingchi Motorway industrial agglomeration GDP points of interest Gaussian process urbanization contracting and expanding city carbon emissions low-carbon city city attributes built-up area thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Remote sensing technology and Geographic Information Systems (GIS) have made significant advancements in the field of urban health, playing crucial roles in monitoring and analyzing urban expansion, land cover changes, urban heat island effects, and flood simulation. These developments indicate that the application of remote sensing and GIS in urban health is continuously deepening, providing powerful tools for urban planning and management. The aim of this reprint is to immerse the reader in the latest methodological models and applications of remote sensing, GIS, and big data in the fields of urban development, healthy cities, and environmental health. This reprint brings together the latest research findings from numerous scholars in the fields of environmental science, urban and rural planning, public health, remote sensing, and GIS applications. Innovations in data methods are evident in these studies, such as the introduction and application of dendrochronological data concepts and analytical methods. There is also research that integrates big data from the internet and various remote sensing data to study urban land use, transportation, public service facilities, and infectious diseases. The advancements in these areas indicate that the application of remote sensing and GIS in the field of urban health is continuously providing powerful tools for urban planning and management. As technology evolves, the application of these technologies in the field of urban health is expected to become more extensive and profound in the future. 2025-02-20T13:33:24Z 2025-02-20T13:33:24Z 2024 book ONIX_20250220_9783725828517_463 9783725828517 9783725828524 https://directory.doabooks.org/handle/20.500.12854/153099 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/10330 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-2852-4 10.3390/books978-3-7258-2852-4 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725828517 9783725828524 204 Basel open access |
| spellingShingle | bacterial foodborne disease global logistic regression geographically weighted logistic regression urban and rural areas vulnerability built environment human health air pollution GIS moderating effect building extraction semantic segmentation group normalization deformable convolution remote sensing images time ring data long time series spatio-temporal characteristics Amazon forest cover urban expansion nighttime light cellular automata urban growth shared socioeconomic pathways allometric scaling land-use change landslide hazard assessment remote sensing data XGBoost algorithm highway pre-trained model night-time lights Google Aggregated Mobility Research Dataset human mobility Africa rural and urban classification GEE RSEI ecological environmental quality Lhasa–Nyingchi Motorway industrial agglomeration GDP points of interest Gaussian process urbanization contracting and expanding city carbon emissions low-carbon city city attributes built-up area thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general Remote Sensing and GIS for Monitoring Urbanization and Urban Health |
| title | Remote Sensing and GIS for Monitoring Urbanization and Urban Health |
| title_full | Remote Sensing and GIS for Monitoring Urbanization and Urban Health |
| title_fullStr | Remote Sensing and GIS for Monitoring Urbanization and Urban Health |
| title_full_unstemmed | Remote Sensing and GIS for Monitoring Urbanization and Urban Health |
| title_short | Remote Sensing and GIS for Monitoring Urbanization and Urban Health |
| title_sort | remote sensing and gis for monitoring urbanization and urban health |
| topic | bacterial foodborne disease global logistic regression geographically weighted logistic regression urban and rural areas vulnerability built environment human health air pollution GIS moderating effect building extraction semantic segmentation group normalization deformable convolution remote sensing images time ring data long time series spatio-temporal characteristics Amazon forest cover urban expansion nighttime light cellular automata urban growth shared socioeconomic pathways allometric scaling land-use change landslide hazard assessment remote sensing data XGBoost algorithm highway pre-trained model night-time lights Google Aggregated Mobility Research Dataset human mobility Africa rural and urban classification GEE RSEI ecological environmental quality Lhasa–Nyingchi Motorway industrial agglomeration GDP points of interest Gaussian process urbanization contracting and expanding city carbon emissions low-carbon city city attributes built-up area thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| topic_facet | bacterial foodborne disease global logistic regression geographically weighted logistic regression urban and rural areas vulnerability built environment human health air pollution GIS moderating effect building extraction semantic segmentation group normalization deformable convolution remote sensing images time ring data long time series spatio-temporal characteristics Amazon forest cover urban expansion nighttime light cellular automata urban growth shared socioeconomic pathways allometric scaling land-use change landslide hazard assessment remote sensing data XGBoost algorithm highway pre-trained model night-time lights Google Aggregated Mobility Research Dataset human mobility Africa rural and urban classification GEE RSEI ecological environmental quality Lhasa–Nyingchi Motorway industrial agglomeration GDP points of interest Gaussian process urbanization contracting and expanding city carbon emissions low-carbon city city attributes built-up area thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general |
| url | ONIX_20250220_9783725828517_463 |